Define, build, and scale enterprise AI capabilities across the shipyards
Establish the foundational AI practice and guide the responsible adoption of AI technologies
Deliver high-value AI solutions aligned with Seaspan’s business objectives
Work closely with IT, Engineering, Operations, Finance, Security, Legal, and Business stakeholders
Coordinate the execution of Seaspan Shipyards’ enterprise AI strategy and roadmap
Serve as the authoritative voice on AI capability, readiness, and feasibility across the organization
Foster a collaborative, inclusive, and high-performing team culture
Define role profiles, skills development plans, and career pathways for AI practitioners
Stay current on advancements in AI, Machine Learning, NLP, LLMs, GenAI, and cloud-based AI platforms
Support the evaluation of emerging AI tools, frameworks, and vendors
Lead the design and implementation of reusable AI architectures, pipelines, and components
Partner with business leaders to translate operational challenges into AI-enabled solutions
Ensure AI initiatives move beyond proof-of-concept into production with clear ownership
Embed ethical AI principles, transparency, and risk mitigation practices into solution design
Act as a bridge between technical teams and business stakeholders

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Applied Mathematics, or a related discipline
Master’s degree in a relevant field is strongly preferred
Relevant certifications in AI, cloud platforms, or data engineering are considered an asset
8+ years of progressive experience in technology, data, analytics, or AI-related roles
5+ years in a technical leadership role, building and leading teams
Demonstrated experience establishing or scaling an AI, analytics, or advanced data practice within a complex organization
Experience delivering AI solutions in shipbuilding, manufacturing, regulated, safety-critical, or industrial environments is highly desirable
Proven track record of moving AI initiatives from concept to production with measurable business impact
Strong understanding of AI and machine learning concepts, including supervised and unsupervised learning, NLP, and LLM-based solutions
Experience with cloud-based AI and data platforms (e.g., Azure, AWS, or equivalent enterprise environments)
Familiarity with AI/MLOps / model lifecycle management, including deployment, monitoring, and retraining
Working knowledge of data architecture, integration patterns, and enterprise systems (ERP, PLM, operational systems)
Understanding of data governance, security, privacy, and responsible AI principles
Ability to evaluate and guide the use of open-source and commercial AI tools

Benefits

annual bonus and pension plan matching
best-in-class health and wellness benefits package
full health care (e.g. unlimited physiotherapy)
dental, vision, life insurance
medical leave coverage
parental leave coverage
wellness/fitness reimbursement for memberships or registration fees
Employee Family Assistance Program (EFAP)
parking included
complimentary shuttle bus Monday through Friday with various pick up and drop off points around North Vancouver

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AIMachine LearningNatural Language ProcessingLarge Language ModelsGenerative AIAI architecturesAI pipelinesdata engineeringdata analyticsdata governance

Soft Skills

collaborationleadershipcommunicationteam culturestakeholder engagementproblem-solvingethical AI principlestransparencyrisk mitigationskills development

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in Data ScienceBachelor’s degree in Applied MathematicsMaster’s degree in a relevant fieldAI certificationscloud platform certificationsdata engineering certifications